- 5 Statistical Traps Data Scientists Should Avoid - Oct 30, 2019.
Here are five statistical fallacies — data traps — which data scientists should be aware of and definitely avoid.
- The Book of Why - Jun 1, 2018.
Judea Pearl has made noteworthy contributions to artificial intelligence, Bayesian networks, and causal analysis. These achievements notwithstanding, Pearl holds some views many statisticians may find odd or exaggerated.
- How To Debug Your Approach To Data Analysis - Dec 29, 2017.
Seven common biases that influence how we understand, use, and interpret the world around us.
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- 4 Common Data Fallacies That You Need To Know - Dec 5, 2017.
In this post you will find a list of common the data fallacies that lead to incorrect conclusions and poor decision-making using data. Here you will find great resources and information so that you can always be reminded of these fallacies when you’re working with data.
- Top KDnuggets tweets, July 29-30: John Tukey coined “Software” and “bit”; Words matter: Adding “terrorism” - Aug 15, 2013.
John Tukey, a great statistician, coined the words "Software" and "bit" ; Words matter: Adding "terrorism" to a poll question makes 10% more people approve NSA; MIT prof. is working on Quantum Machine Learning; 4 Common Stats Errors to avoid: 1. Base Rate Fallacy 2. Extrapolation 3. Correlation != Causation